Jpmorgan Chase Bank, N.a.

Yue Guo

Tucker Richard Balch

Antigoni Ourania Polychroniadou

A method for providing a secure aggregation protocol that facilitates federated learning of machine learning models while protecting privacy of individual data sets associated with participants is provided. The method includes: a setup phase by which public key—secret key pairs are used to verify signatures and facilitate secure transmissions of encrypted messages that include datasets to be aggregated; and an aggregation phase by which a random oracle/hash function is used to facilitate the aggregation of newly submitted datasets into the preexisting aggregated dataset.

Method and system for secure aggregation protocol for protecting privacy of individual data sets

A method for learning a shared machine learning model while preserving privacy of individual participants is provided. The method includes: receiving, from each of a group of users, an encrypted user input; when a number of user inputs is greater than or equal to a threshold, transmitting, to each user, a list of the group of users; receiving, from each user, a message indicating a mutual agreement regarding a shared secret among the group; and when a number of received messages indicating the mutual agreement is greater than or equal to the threshold, determining information about the shared machine learning model by combining the received encrypted user inputs. The shared machine learning model facilitates a secure multi-party computation of a function that generates an updated version of the shared machine learning model.

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Jersey City, NJ, United States of America

Yue Guo